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const axios = require('axios');
const fs = require('fs');
const path = require('path');
// helper function to help you convert your local images into base64 format
async function toB64(imgPath) {
const data = fs.readFileSync(path.resolve(imgPath));
return Buffer.from(data).toString('base64');
}
const api_key = "YOUR API-KEY";
const url = "https://api.segmind.com/v1/claude-opus-4.7";
const data = {
"messages": [
{
"role": "user",
"content" : "tell me a joke on cats"
},
{
"role": "assistant",
"content" : "here is a joke about cats..."
},
{
"role": "user",
"content" : "now a joke on dogs"
},
]
};
(async function() {
try {
const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } });
console.log(response.data);
} catch (error) {
console.error('Error:', error.response.data);
}
})();An array of objects containing the role and content
Could be "user", "assistant" or "system".
A string containing the user's query or the assistant's response.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
Claude Opus 4.7 is Anthropic's most capable generally available large language model, released in April 2026. Built as a major upgrade over Claude Opus 4.6, it delivers state-of-the-art performance in agentic coding, multidisciplinary reasoning, scaled tool use, and computer use. The model features a 1M-token context window, enabling it to process massive codebases, lengthy documents, and complex multi-step workflows in a single session. With substantially improved vision capabilities supporting up to 3.75 megapixels, Claude Opus 4.7 can analyze high-resolution images, charts, and interfaces with exceptional accuracy.
Claude Opus 4.7 scores 87.6% on SWE-bench Verified (up from 80.8% with Opus 4.6), 64.3% on SWE-bench Pro, and 70% on CursorBench. It introduces the xhigh effort setting for finer control over reasoning depth versus latency. The model excels at sustained multi-hour autonomous workflows, recovering gracefully from tool failures rather than halting. It also follows instructions more precisely than its predecessor, interpreting them literally rather than loosely.
Claude Opus 4.7 is ideal for agentic software development where the model navigates codebases, writes tests, and resolves issues autonomously. It handles complex research and analysis across long documents with its 1M-token context. Developers use it for multi-step tool orchestration, automated code review, and high-resolution image analysis. It also excels at document understanding, slide and interface design, and long-horizon planning tasks that require sustained context retention across sessions.
For best results, provide detailed context and break complex tasks into structured steps. Use the image parameter for visual tasks — the high-resolution support means you can pass full-page screenshots or detailed charts without downscaling. For coding tasks, include relevant file contents and clear acceptance criteria. The xhigh effort setting works well for harder problems requiring deeper reasoning.
How does Claude Opus 4.7 compare to GPT-5.4? Claude Opus 4.7 leads on SWE-bench Verified and agentic reasoning benchmarks, outperforming GPT-5.4 and Gemini 3.1 Pro on coding tasks.
What is the context window size? Claude Opus 4.7 supports up to 1 million tokens of context, suitable for processing entire codebases or lengthy research documents.
Does Claude Opus 4.7 support image input? Yes, it accepts images up to 2,576 pixels on the long edge (approximately 3.75 megapixels), a significant upgrade from Opus 4.6's 1.15 megapixel limit.
What is the xhigh effort setting? A new reasoning depth option between high and max that gives developers finer control over how deeply the model reasons before responding, balancing quality against latency.
Is Claude Opus 4.7 available via API? Yes, it is available through the Anthropic API, Amazon Bedrock, Google Cloud Vertex AI, Microsoft Foundry, and on Segmind.